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Biomedical subjects

H Grabowski

Publications and source records attributed to H Grabowski.

16 recordsLinked to original sources

The role of cost-effectiveness analysis in managed-care decisions.

This article considers the role of cost-effectiveness studies in the formulary and disease-state management decisions of managed-care entities. In a recently published symposium volume [Soc Sci Med 1997; 45 (4): 505-647], US managed-care entities were found to be among the leaders in applying cost-effectiveness studies to healthcare decisions. At the same time, a number of barriers were identified that hinder their wider usage in the managed-care sector. These factors are analysed in this paper along with the prospects for future changes. The potential roles for government policy in this area are also discussed in the final section of the article.

Chemistry, Pharmaceutical↗

Planning and simulation of medical robot tasks.

Complex techniques for planning and performing surgery revolutionize medical interventions. In former times preoperative planning of interventions usually took place in the surgeons mind. Today's new computer techniques allow the surgeon to discuss various operation methods for a patient and to visualize them three-dimensionally. The use of computer assisted surgical planning helps to get better results of a treatment and supports the surgeon before and during the surgical intervention. In this paper we are presenting our planning and simulation system for operations in maxillo-facial surgery. All phases of a surgical intervention are supported. Chapter 1 gives a description of the medical motivation for our planning system and its environment. In Chapter 2 the basic components are presented. The planning system is depicted in Chapter 3 and a simulation of a robot assisted surgery can be found in Chapter 4. Chapter 5 concludes the paper and gives a survey about our future work.

Algorithms↗

Pharmacy benefit management, cost-effectiveness analysis and drug formulary decisions.

Pharmacy benefit management companies (PBMs) have evolved over the past decade in response to the increased demand for health care cost containment. Their activities include the implementation of drug formularies and the negotiation of rebates from manufacturers. Our analysis of this industry is based on interviews and materials provided by the top five ranked PBM companies which account for over 80% of beneficiaries covered within formulary plans. The formularies of these companies are relatively inclusive, but they are becoming more restrictive over time. At present the use of cost-effectiveness (C-E) studies in the formulary decisions of PBMs has been limited. In this regard, the surveyed PBMs emphasized that most C-E studies have not compared therapeutic substitutes in populations with characteristics that are similar to those of their clients. Pharmacy benefit management companies also have had strong incentives to focus narrowly on drug costs because they typically manage drug benefits on a "carved-out" basis. However, PBMs anticipate a growing future role in the integrated management of patient care (disease management) for certain high cost chronic diseases and conditions. All of the leading firms we surveyed have disease management programs in development. The importance of C-E studies to PBM decisions is expected to increase significantly as disease management programs are implemented. The data infrastructure inherent to the PBM industry and the increasing number of employees with advanced training in pharmacoeconomics will permit firms to perform their own internal C-E studies. They are also establishing various alliances and joint ventures with drug manufacturers, health maintenance organizations, and academic institutions to perform these analyses. The leading PBMs tend to favor active participation in the development of methodological approaches to C-E studies over government regulations such as those proposed by the FDA in 1995.

Cost Control↗

The effect of pharmacoeconomics on company research and development decisions.

There is a strong rationale for integrating pharmacoeconomics into research and development (R&D) project selection and termination decisions. The average cost for the typical new drug introduction now exceeds $US300 million. Furthermore, a growing proportion of phase III projects are terminated because of economic factors relative to efficacy and safety concerns. While the use of pharmacoeconomic studies by payers is still evolving, the pressures on firms to show that new products are cost effective will only intensify in future periods. Accordingly, it is important for firms to begin analysing the cost effectiveness of new drug candidates early in the R&D process. The cost effectiveness of a new therapy can be simulated prior to clinical testing using different assumptions about the efficacy, tolerability, pricing and formulation of the new therapy. These models can be refined and updated as data become available from clinical testing and other sources. A key objective is to make uncompetitive projects fail sooner while channelling development resources to projects with high expected returns. Cost-effectiveness analysis should be an integral component of the firms's strategic action plan and its return on investment analyses.

Cost-Benefit Analysis↗

Longer patents for increased generic competition in the US. The Waxman-Hatch Act after one decade.

The 1984 Waxman-Hatch Act had two main objectives. Title I was designed to promote price competition by establishing an abbreviated new drug application (ANDA) process for generic market entry. Title II was designed to encourage drug innovation by restoring some of the patent life lost during the lengthy FDA regulatory process. In this paper, we consider whether these twin objectives have been realised during the first decade of the Act's existence. First, we investigate the pattern of generic and brand name prices and market shares for the major products whose patents expired between 1984 and 1993. A regression model indicates that generic competition has been intensifying significantly in recent periods. Major brand name products now typically lose more than half their market share within the first year after patent expiration. In addition, we examine changes in patent protection for new chemical entities introduced over the period 1984 to 1993. For 1991 to 1993 new drug introductions, the average effective patent life was 11.8 years with 2.3 years resulting from Waxman-Hatch extensions. In the final section of the paper, we consider how the US law compares with that in Europe and discuss possible legislative improvements in the 1984 Act.

Cost Control↗

High level production of human growth hormone in the milk of transgenic mice: the upstream region of the rabbit whey acidic protein (WAP) gene targets transgene expression to the mammary gland.

The 5' flanking region (6.3 kb) of the rabbit WAP (rWAP) gene possesses important regulatory elements. This region was linked to the human growth hormone (hGH) structural gene in order to target transgene expression to the mammary gland. Thirteen lines of transgenic mice were produced. Milk could be collected from six lines of transgenic mice. In five of them, hGH was present in the milk at high concentrations ranging from 4 to 22 mg ml-1. hGH produced by the mammary gland comigrated with hGH of human origin. It was biologically active, and through its prolactin-like activity induced lactogenesis when introduced into mammary culture media. Two of these mouse lines were studied further. hGH mRNA was only detected in the mammary gland during lactation. In the seven other transgenic lines, hGH was present in the blood of cyclic females. The prolactin-like effect of hGH in these mice probably induced female sterility, and milk could therefore not be obtained. In two lines studied in more detail, the mammary gland was the main organ producing hGH, even in cyclic mice. Low ectopic expression was detected in other organs which varied from one line to the other. This was probably due to the influence on the transgene of the site of integration into the mouse genome. In the 13 lines studied, high mammary-specific hGH expression was not correlated to the transgene copy number. The rWAP-hGH construct thus did not behave as an independent unit of transcription. However, it can be concluded that the 6.3 kb flanking region of the rWAP gene contains regulatory elements responsible for the strong mammary-specific expression of hGH transgene, and that it is a good candidate to control high levels of foreign protein gene expression in the mammary gland of lactating transgenic animals.

Animals↗

Rabbit whey acidic protein concentration in milk, serum, mammary gland extract, and culture medium.

Rabbit whey acidic protein has been purified from whey using an AcA54 column. The purified whey acidic protein had an amino acid composition in agreement with the previously defined cDNA sequence. An antibody against whey acidic protein was raised in guinea pig. This antibody did not crossreact with mouse or cow milk or with rabbit alpha s1-casein and beta-casein. Whey acidic protein concentration was measured in rabbit milk using the antibody with a radioimmunoassay. The concentration of whey acidic protein in rabbit milk was 15 mg/ml, whereas the concentrations of alpha s1-casein and beta-casein were 16 and 45 mg/ml, respectively. The concentration of the three proteins was also evaluated in culture medium of rabbit primary mammary cells. The three proteins were induced by prolactin alone. Glucocorticoids amplified the prolactin effect on whey acidic protein more intensively than on caseins. The three proteins were present in mammary extract from virgin rabbit. The concentration of these proteins was lower at d 8 and 14 of pregnancy, and it was very high at d 25 of pregnancy. Whey acidic protein was undetectable in blood of virgin, weaned, and midpregnant females and of males. Whey acidic protein was present in blood of lactating rabbits, but alpha s1-casein and beta-casein were not detectably present in rabbit blood at the examined physiological states.

Amino Acids↗